Mapping of the Insomnia Severity Index and other sleep measures to EuroQol EQ-5D health state utilities

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This study sought to map the Insomnia Severity Index (ISI) and symptom variables onto the EQ-5D. Methods A cross-sectional survey was conducted among adult US residents with self-reported sleep problems. Respondents provided demographic, comorbidity, and sleep-related information and had completed the ISI and the EQ-5D profile. Respondents were classified into ISI categories indicating no, threshold, moderate, or severe insomnia. Generalized linear models (GLM) were used to map the ISI's 7 items (Model I), summary scores (Model II), clinical categories (Model III), and insomnia symptoms (Model IV), onto the EQ-5D. We used 50% of the sample for estimation and 50% for prediction. Prediction accuracy was assessed by mean squared errors (MSEs) and mean absolute errors (MAEs). Results Mean (standard deviation) sleep duration for respondents (N = 2,842) was 7.8 (1.9) hours, and mean ISI score was 14.1 (4.8). Mean predicted EQ-5D utility was 0.765 (0.08) from Models I-III, which overlapped with observed utilities 0.765 (0.18). Predicted utility using insomnia symptoms was higher (0.771(0.07)). Based on Model I, predicted utilities increased linearly with improving ISI (0.493 if ISI = 28 vs. 1.00 if ISI = 0, p < 0.01). From Model II, each unit decrease in ISI summary score was associated with a 0.022 (p < 0.001) increase in utility. Predicted utilities were 0.868, 0.809, 0.722, and 0.579, respectively, for the 4 clinical categories, suggesting that lower utility was related to greater insomnia severity. The symptom model (Model IV) indicated a concave sleep-duration function of the EQ-5D; thus, utilities diminished after an optimal amount of sleep. The MSEs/MAEs were substantially lower when predicting EQ-5D > 0.40, and results were comparable in all models. Conclusions Findings suggest that mapping relationships between the EQ-5D and insomnia measures could be established. These relationships may be used to estimate insomnia-related treatment effects on health state utilities.

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Publié le 01 janvier 2011
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Gu et al . Health and Quality of Life Outcomes 2011, 9 :119 http://www.hqlo.com/content/9/1/119
R E S E A R C H Open Access Mapping of the Insomnia Severity Index and other sleep measures to EuroQol EQ-5D health state utilities * Ning Yan Gu 1 , Marc F Botteman 1 , Xiang Ji 1 , Christopher F Bell 2 , John A Carter 1 and Ben van Hout 3,4
Abstract Background: This study sought to map the Insomnia Severity Index (ISI) and symptom variables onto the EQ-5D. Methods: A cross-sectional survey was conducted among adult US residents with self-reported sleep problems. Respondents provided demographic, comorbidity, and sleep-related information and had completed the ISI and the EQ-5D profile. Respondents were classified into ISI categories indicating no, threshold, moderate, or severe insomnia. Generalized linear models (GLM) were used to map the ISI s 7 items (Model I), summary scores (Model II), clinical categories (Model III), and insomnia symptoms (Model IV), onto the EQ-5D. We used 50% of the sample for estimation and 50% for prediction. Prediction accuracy was assessed by mean squared errors (MSEs) and mean absolute errors (MAEs). Results: Mean (standard deviation) sleep duration for respondents (N = 2,842) was 7.8 (1.9) hours, and mean ISI score was 14.1 (4.8). Mean predicted EQ-5D utility was 0.765 (0.08) from Models I-III, which overlapped with observed utilities 0.765 (0.18). Predicted utility using insomnia symptoms was higher (0.771(0.07)). Based on Model I, predicted utilities increased linearly with improving ISI (0.493 if ISI = 28 vs. 1.00 if ISI = 0, p < 0.01). From Model II, each unit decrease in ISI summary score was associated with a 0.022 (p < 0.001) increase in utility. Predicted utilities were 0.868, 0.809, 0.722, and 0.579, respectively, for the 4 clinical categories, suggesting that lower utility was related to greater insomnia severity. The symptom model (Model IV) indicated a concave sleep-duration function of the EQ-5D; thus, utilities diminished after an optimal amount of sleep. The MSEs/MAEs were substantially lower when predicting EQ-5D > 0.40, and results were comparable in all models. Conclusions: Findings suggest that mapping relationships between the EQ-5D and insomnia measures could be established. These relationships may be used to estimate insomnia-related treatment effects on health state utilities. Keywords: Insomnia, Mapping, Insomnia Severity Index, EQ-5D
Introduction difficulties initiating/maintaining sleep, early awakening, Insomnia is a disorder broadly defined by difficulty with and non-restorative or poor quality sleep [3]. sleeping. It may be characterized by 1) primary insom- The prevalence of insomnia in the adult population nia, without underlying medical cause; 2) secondary ranges from 10% to 30% [1,4-6]. Insomnia is associated insomnia, with presence of an underlying medical cause; with substantial burden to patient and society. Persistent 3) acute insomnia, symptoms with a short duration or; or prolonged sleeping problems have been associated 4) chronic insomnia, symptoms with a long duration with worsened health outcom es including reduced pro-[1,2]. Patients with insomnia commonly complain of ductivity or physical/social functioning, increased risk of occupational accidents or major depression/anxiety dis-orders, poorer health-relat ed quality-of-life (HRQoL) and, increased health care costs [7-13]. Meanwhile, 1 *PChaorrrmeserpitonNdoertnhce:Anmgeruic@ap,hLaLrCm,4e3ri5t.0coEamstWestHighway,Suite430,Bethesda, sleep-related conditions have often been under-diag-MD 20814, USA nosed and under-treated [14]. Full list of author information is available at the end of the article © 2011 Gu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.